radar networks Search Result 3
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Deep learning based camera/radar sensor fusion technology for road side unit (RSU) applications
Based on deep learning camera/radar object detection and tracking technology, the proposed road side unit (RSU) system has achieved over 95% vehicle detection accuracy within 100m detection range in the processing performance of 10fps under nVidia Jetson Xavier platform. Compared to the 32-beam lidar based RSU, the proposed RSU achieves 97% reduction of sensor cost that exhibits high competitiveness in deployment cost. The proposed RSU system has been verified in fields and we are now cooperating with an industry partner to deploy the RSU system in both Tainan and Tao-Yuan cities.
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AI deep compression toolchain and Hybrid-fixed point CNN accelerator
Assisted by in-house AI deep compression toolchain (ezLabel, ezModel, ezQUANT, ezHybrid-M), the proposed technology supports automatic AI model design and optimization with the integrated performance of 120x model size reduction and 70x power reduction in 2D CNN model, and develops a world-first 1/2/4/8-bit CNN model realized by the developed high efficiency Hybrid fixed point CNN NPU (Hybrid-NPU), which has been verified in Xilinx ZCU102 FPGA and achieves the performance up to 2.5 TOPS(8-b)/ 20TOPS(1-b)@28nm technology running at 550MHz and 4TOPS/W energy efficiency.
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Computer Vision Research Center, National Yang-Ming Chiao-Tung university
Development of AI Platform for Smart Drone - Intelligent Flight: Due to its high mobility and the ability to fly in the sky, the drone has inspired more and more innovative applications/services in recent years. The goal of this project is to resolve the problem of blindly flying an unmanned aerial vehicle (UAV, which a drone in our case) when it is out of human sight or the range of wireless communication, and three major research and development directions will be considered in this project. Three artificial intelligence (AI) technologies, namely, smart sensing, smart control, and smart simulation, are applied in this project. Smart sensing - a flight system is developed, which can avoid the obstacles, complete a flight mission, and land safely. Smart control - an intelligence flight control system and a light-weighted somatosensory vest are developed. Smart simulation - a cost-effective training system and a 3D model simplification method are designed.
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